3 papers
cs.LG2026
GraphPL: Leveraging GNN for Efficient and Robust Modalities Imputation in Patchwork Learning
Xingjian Hu, Zuoyu Yan, Jianhua Zhu +3
Current research on distributed multi-modal learning typically assumes that clients can access complete information across all modalities, which may not hold in practice. In this p…
cs.LG2025
Enhancing Graph Representation Learning with Localized Topological Features
Zuoyu Yan, Qi Zhao, Ze Ye +5
Representation learning on graphs is a fundamental problem that can be crucial in various tasks. Graph neural networks, the dominant approach for graph representation learning, are…
cs.LG2024
An Efficient Subgraph GNN with Provable Substructure Counting Power
Zuoyu Yan, Junru Zhou, Liangcai Gao +2
We investigate the enhancement of graph neural networks' (GNNs) representation power through their ability in substructure counting. Recent advances have seen the adoption of subgr…